Evidence map›Paper›PMID 32185902›Full record

ReviewCellular microbiology2020

Mammalian membrane trafficking as seen through the lens of bacterial toxins.

Francisco Sarmento Mesquita, F Gisou van der Goot, Oksana A Sergeeva

Open access · bronzeAbstract readReview
In one paragraph

Review in Cellular microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Francisco Sarmento MesquitaGlobal Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland.ORCID 0000-0002-3777-825X
F Gisou van der GootGlobal Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland.ORCID 0000-0002-8522-274X
Oksana A SergeevaGlobal Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland.ORCID 0000-0002-4830-0518
Institute for Work and Health · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental question of eukaryotic cell biology is how membrane organelles are organised and interact with each other. Cell biologists address these questions by characterising the structural features of membrane compartments and the mechanisms that coordinate their exchange. To do so, they must rely on variety of cargo molecules and treatments that enable targeted perturbation, localisation, and labelling of specific compartments. In this context, bacterial toxins emerged in cell biology as paradigm shifting molecules that enabled scientists to not only study them from the side of bacterial infection but also from the side of the mammalian host. Their selectivity, potency, and versatility made them exquisite tools for uncovering much of our current understanding of membrane trafficking mechanisms. Here, we will follow the steps that lead toxins until their intracellular targets, highlighting how specific events helped us comprehend membrane trafficking and establish the fundamentals of various cellular organelles and processes. Bacterial toxins will continue to guide us in answering crucial questions in cellular biology while also acting as probes for new technologies and applications.

Indexed as

Host Microbial InteractionsAnimalsBacterial ToxinsCell BiologyCell MembraneCell MovementMammalsProtein TransportBacterial Toxinscell membranemechanism of actiontoxinstrafficking

Identifiers

PMID32185902
PMCPMC7154709
OpenAlexW3011009689

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.